The chief aims of this project are to advance understanding of the epidemiology of lymphatic filariasis (LF) transmission by anopheline mosquitoes and its control using annual mass drug administration (MDA) strategies in Papua New Guinea (PNG) and elsewhere, and to develop and apply effective model-based decision support tools for optimizing the design and evaluation of parasite control at the community level. The research will take advantage of past and new field data to be collected by a recently funded NIH ICIDR program, on the impacts of MDA-based strategies, including the addition of vector control to MDA, on filariasis transmission in PNG endemic communities, in order to meet four specific aims: 1) development and validation of a mathematical model specific to describing the population dynamics of LF by anopheline mosquitoes in PNG, 2) estimation and validation of intervention endpoints via the comparative analysis of deterministic versus stochastic versions of the derived model, 3) testing model predictions of the impacts of MDA-based strategies, including MDA plus vector control by the use of Insecticide-Treated Bednets (ITNs), using empirical data on the effects of these interventions collected by the new ICIDR program, and 4) development and implementation of a software tool linking the constructed model and data from endemic sites to facilitate the undertaking of optimal planning, evaluation and management of LF control programs. The proposed research will thus be based on field data available and to be collected by the collaborators on this project on LF interventions, the analyses/modeling of these data and data describing infection dynamics in both the human and vector populations (data on the latter to be collected by conducting vector feeding experiments in this project), and theoretical analyses. The major outputs from this work of vital significance to the global LF elimination program will be: 1) the development of models of LF transmission by anopheline vectors based on various markers of infection, 2) the derivation of endpoints for parasite elimination, 3) the development of model-based evaluation protocols for assessing program effectiveness, 4) the taking of a population dynamic approach to economic assessments of LF control strategies, 5) the dynamic evaluation of including vector control via ITNs to MDA programs, and 6) the construction of a model- and data- integrated software tool for aiding the optimal design and evaluation of LF control programs.